EMAN: Optimization-Driven Capacity Growth through Path Emergence in Multi-Task Learning
arXiv:2608.16930v1 Announce Type: new Abstract: Existing multi-task learning methods rely on hard sharing, multiple paths or experts, adaptive sharing, and dynamic expansion. However, their capacity changes are usually constrained by predefined structures or triggered by task boundaries and…